Applicant(s)

Size of team/newsroom:small

Categories:

Description

Data comes in all forms. For this project, we analyzed the colors of fall leaves changing in Connecticut. We scraped thousands of photos and figured out the core color from the leaves and built a list of that we paired in a visualization with the actual photos. This let the readers see exactly when they could expect the colors to start changing by letting them explore years of colors and photos themselves. We also spoke with experts to figure out the overall geographical trend.

What makes this project innovative? What was its impact?

It was a fun color-based project. It required scraping photos and figuring out a way to extract color details to build out a dataframe. We had very different methods, such as hover, but were limited by wanting to be functional on all screens. Figuring out how to pull in thousands of photos was also a challenge. The impact was that the state (where we got the photos from) realized there was a different way to leverage the ozone cameras they had to build out a searchable/scrubbable archive. While doing the project, we figured out a way to reconstruct images programmatically to visualize time passing as a movie or a gif. The process will be open-sourced as an R script very soon.

Technologies used for this project:

R for scraping and extracting the color data and resizing the images, as well as creating the locator map graphics. Javascript and CSS to build out the gradient/photo explorer.